Binary sparse nonnegative matrix factorization

Yuan, Yuan, Li, Xuelong, Pang, Yanwei, Lu, Xin and Tao, Dacheng (2009). Binary sparse nonnegative matrix factorization. IEEE Transactions on Circuits and Systems For Video Technology, 19 (5), pp. 772-777.

Abstract

This paper presents a fast part-based subspace selection algorithm, termed the binary sparse nonnegative matrix factorization (B-SNMF). Both the training process and the testing process of B-SNMF are much faster than those of binary principal component analysis (B-PCA). Besides, B-SNMF is more robust to occlusions in images. Experimental results on face images demonstrate the effectiveness and the efficiency of the proposed B-SNMF.

Publication DOI: https://doi.org/10.1109/TCSVT.2009.2017306
Divisions: Engineering & Applied Sciences > Computer Science
Life & Health Sciences > Pharmacy
Uncontrolled Keywords: binary principal component analysis,binary sparse nonnegative matrix factorization,face images,fast part-based subspace selection algorithm,image occlusions,Electrical and Electronic Engineering,Media Technology
Full Text Link: http://www.nlpr ... ers/kz/gk13.pdf
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
http://ieeexplo ... rnumber=4801604 (Publisher URL)
Published Date: 2009-05
Authors: Yuan, Yuan
Li, Xuelong
Pang, Yanwei
Lu, Xin
Tao, Dacheng

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